Wednesday, December 28, 2016

As the year is coming to an end I’d like to share a few thoughts on what we’ll be looking for in the SaaS world in 2017. This is not meant to be an exhaustive enumeration but rather a brief outline of a few big themes that I feel particularly strongly about.

1) Viral growth and/or negative churn

In the last couple of years I’ve come to the opinion that in order to build a SaaS unicorn you need to have either (a) a highly viral customer acquisition engine or (b) significant negative net churn (that is, a dollar retention rate significantly above 100%). The rationale behind this statement, which might seem odd at first sight, is actually simple math. If you don’t have negative net churn you’re losing an increasing amount of MRR every month to churn, simply because your churn rate is applied to an ever-increasing base. That means that as long as you have positive net churn, you’ll have to add an increasing amount of new MRR from new customers every month just to offset churn. As you’re getting bigger and bigger it will become extremely difficult to maintain a high growth rate if you have to replace an ever-increasing amount of churn – unless you have an inherently viral product.

At a somewhat theoretical level, what I’m saying is that since net churn MRR grows as a function of your MRR base, you better have a mechanism that lets you add new MRR as a function of your existing base as well. I know this is a somewhat simplified way of looking at it and I’m sure there are a few exceptions to this rule, but I’m convinced that almost all SaaS startups that want to become big should strive for viral growth, negative churn, or both.

Companies like Slack or Zendesk have shown that a superior user experience can provide a decisive competitive advantage and can become a critical success factor for SaaS businesses. Pundits might object that you don’t win enterprise customers by having a prettier interface. I think that’s shortsighted for at least two reasons.

First, user experience is not only about making the UI more beautiful. As legendary UX expert Jakob Nielsen defines it, “user experience encompasses all aspects of the end user's interaction with a company, its services and its products”. An excellent user experience requires an elegant product that meets the needs of the customer and is a joy to use, but it goes beyond that. The design of your marketing website, the tone of voice of your marketing emails, interactions with customer service – all of this is part of the experience that you offer.

Second, today more and more buying decisions are made by the actual users of the software (e.g. someone in marketing looking for a marketing automation solution) as opposed to the IT department. When the buyer is also the user, usability becomes one of the key decision criteria.

This decentralization of software buying, which has led to the consumerization of enterprise software both from a product as well as a go-to-market perspective, is maybe the most important driver of change in the software industry that we’ve seen in the last 5-10 years. But it’s far from over. Millennials arguably have even less tolerance for slow, bloated, ugly enterprise software. If you grew up with UBER and Spotify, if you’ve never ordered a cab by phone and never went to a store to order a CD, chances are you expect your work software to work flawlessly as well. :-) As millennials continue to rise up the ranks, a focus on great design and a delightful user experience will become even more important for software companies.

Two of our most successful SaaS investments to date, Zendesk and Typeform, owe a large part of their success to what I like to call a “10x” improvement in user experience over the status quo. It will be extremely interesting to see which companies can accomplish a similar quantum leap in 2017 and how it will look like. Will it be a SaaS solution with voice as the primary form of input? A mobile-first SaaS app that truly leverages the smartphone’s camera, sensors and other applications to provide a 10x better user experience? Or a software with a conversational interface, powered by a bot? I don’t have the answer, but I’m pretty sure that new ways to input data – methods that are more natural than dropdown menus or smartphone keyboards – will be a part of it.

Up until recently, the main job of software was to make people more efficient by digitizing paper-based processes, doing calculations and enabling more efficient communication inside and between companies. This has led to huge efficiency gains, and I honestly have no idea how companies used to be operated without computers until 40-50 years ago.

And yet, the biggest disruption is still ahead of us. I am, of course, talking about artificial intelligence (AI). How long it will take until AI will reach human intelligence – or if that’s never going to happen – is an extremely interesting topic that goes far beyond the scope of this post (and of course one that I’m not an expert in). It’s safe to assume, though, that software is getting better and better at more and more tasks which were previously thought to be impossible for computers to learn. Watson’s victory against two “Jeopardy” champions a few years ago and AlphaGo’s win against one of the best Go players are two legendary examples, but there are lots of other, less publicized cases, of computers winning against humans.

If close to 50% of jobs will be done by computers in the not too distant future, as an Oxford University study suggests, this will of course have unprecedented consequences for our society. How those consequences will look like, and if the net impact will be positive or negative for most people, is another extremely interesting topic that I’m not going to delve into here. What’s clear is that this disruptive force will create enormous opportunities for SaaS companies.

With today’s software it can sometimes be hard for a SaaS startup to prove the ROI of its product to prospective customers. Putting a dollar sign on the efficiency gains that a customer can realize by using your software can be difficult, and your product may provide lots of pretty intangible benefits that are hard to quantify. Now imagine that your SaaS solution allows your customers to get work done with significantly less people or maybe no people at all. In that case, the ROI will be pretty obvious.

What if future versions of sales automation software will not make your sales force more efficient but become your sales force? I can’t imagine how bots could take over sales calls … or wine and dine with a client. :) But think about jobs like web-based prospecting, lead qualification or email campaigns and the idea starts to sound a lot less far-fetched.

Although we developed a strong interest in AI in the last few years we have not yet seen a large number of “AI startups” that we fell in love with (one notable exception is our portfolio company Candis, which is automating accounting work). This could be because the industry is still at a nascent stage or because it’s still early days for us in terms of learning and developing an investment thesis around AI, or both. In any case, we’re excited to spend more time on this topic in the coming year!

Wednesday, November 23, 2016

In case you haven't started to think about your plan for 2017 yet, now's the time. To help you a little bit with your planning, here are three little tools that you might find useful. If you're a long-time reader of this blog, you may have seen them before.

1. Growth Calculator

This little tool allows you to enter your MRR as of the end of 2016 and a target growth factor for 2017. It then calculates your MRR target for the end of 2017 and shows you three different growth paths that lead to that goal. One is based on linear growth, one on exponential growth and the third one shows a trajectory between the linear and the exponential path.

Please note that although this Google Sheet may look a bit like a financial plan, it's not meant to be your plan. :) To create a credible and realistic plan, you need to have a "bottom-up" projection of your growth drivers (e.g. your conversion funnel, distribution channels and sales team quotas). What this little calculator can do is quickly give you a sense for how much MRR you have to add each month in 2017 in order to reach your growth targets, so you can use it to play around with different scenarios and assumptions.

2. Sales Team Hiring Plan

This tool helps you find out how many sales people you need to hire in 2017 based on your growth targets and other import inputs such as your MRR churn rate, your sales team's quota, ramp-up times, etc.

The model is based on an exponential growth path (i.e. #2 from the Growth Calculator above), i.e. it works with a constant m/m growth rate, which you can set in cell D11 and D12 for 2017 and 2018, respectively. You can easily adjust this to a different growth path by changing row 22 accordingly.

One of the things which the model doesn't take into account is employee turnover. In sales teams, employee churn can be significant, both because not every sales person that you hire will work out and because the average tenure of an AE might be only, say, two years. When I tried to add this to the model it became too complex for what I think should stay a pretty simple template. I might give it another go later. In the meantime, I'd recommend that when you build your own hiring plan, assume that if you need x AEs you'll have to hire n*x AEs, and that n is probably something between 1.1 and 2, depending on how good you are at hiring salespeople.

3. Financial Plan

This template helps you create a full financial plan that includes everything from revenue modeling to costs projections and headcount planning. If you look at it for the first time, it might look a little terrifying. I did try to keep it as simple as possible, but if you prefer a simpler version I also have an older, less sophisticated alternative.

Monday, September 19, 2016

So you’ve recently started a company, you’ve started to talk to angel investors and seed funds about your seed round, and suddenly a large VC appears on the scene and wants to invest. What should you do?

First of all, congrats. If a large fund wants to invest in your startup, that’s a great validation. Second, if you can get the brand, credibility, network and support of a Tier 1 VC into your startup early on, that can be extremely beneficial. So you should definitely consider it. It’s a complicated question, though, and you have to carefully consider the pros as well as the cons.

In this post I’ll try to shed some light on this question. As a disclosure and caveat, being a seed VC I’m not a disinterested observer, since we occasionally compete with bigger funds on seed deals. I’ll try to be as unbiased as possible, and if you disagree with my views you’re more than welcome to chime in, e.g. in the comments section.

Further below is a simple matrix that might be helpful to founders as they consider having a large fund participate in their seed round. But first, in case you’re not familiar with the issue, here’s a quick primer. If you know what the “signaling risk” debate is about, you can skip the next fext few paragraphs.

Some years ago, many large VCs – $200-400M+ funds that typically invest anything from $5M to $20M or more in Series A/B/C rounds – started to make seed investments, placing a sometimes large number of oftentimes tiny bets in very early-stage companies. The intention behind these investments is not to make a great return on these initial bets. Consider a $400M fund that invests, say, $250k in a startup. Even if that investment yields a rare and spectacular 100x return, it means only $25M in exit proceeds for the fund. That’s a lot of money for you and me, but not a lot of money for a $400M fund that needs around $1.2-1.5B of exit proceeds to deliver a good return to its LPs. If a large fund writes a tiny check (i.e. tiny relative to the size of the fund), there’s almost zero chance that the investment will move the needle for the fund.

So what is the intention behind these investments? The answer is access to Series A rounds. The idea is that one invests, say, $250k in 50 companies, watch them carefully and then try to lead (and maybe pre-empt) the Series A rounds of the ones that do best. Even if most of these seed bets don’t work out – as long as the VC gained access to a handful of great Series A deals, it’s money well spent. At least superficially it makes a lot of sense for large VCs to employ such a strategy. Whether it’s also a good strategy in the long run, or if it leads to brand dilution and eventually adverse selection, is a different question and beyond the scope of this post.

For entrepreneurs, more VCs investing into seed rounds means easier access to capital. And as mentioned before, founders who raise a seed round from a large VC also get the benefit of getting a brand name VC on board early on and potentially they can tap into the firm’s support network. So far, so good - sounds like a win/win.

The downside of taking a small check from a large investor is what’s called “signaling risk”. What this refers to is the situation that arises when you want to raise your Series A round and your VC doesn’t want to lead. In that case, any outside investor who you’re talking to will wonder why your existing investor – who as an insider has or could have a great understanding of the business – doesn’t want to invest. Everybody in the market knows that if a large VC invests small amounts the purpose is optionality, so if the VC then doesn’t try to seize the option, people will wonder why.

There might be good reasons why your VC doesn’t want to invest despite the fact that your company is doing well, and you might still be able to convince other investors to take the lead. But as you can imagine, it won’t be easy: Investors see large numbers of potential investments and have to decide quickly and based on incomplete information which ones they take a closer look at. That’s why they are highly receptive to any kind of signal. If they hear that the large VC who did the seed round doesn’t want to do the Series A, they might not even want to take the time to dig in deeper and might pass right away. As Chris Dixon wrote in a post some years ago, “If Sequoia gave you seed money before but now doesn’t want to follow on, you’re probably dead.”

Long story short, raising a seed round from a large VC has clear upside but also big risks. How should founders decide?

Let’s look at the data. CBInsights has some very interesting data which shows that statistically, startups that raised a seed round from a large VC have a higher chance of raising a Series A later on. What the data doesn’t tell us is whether that is (A) because these startups benefitted from having a large VC on board early on or (B) because they were better companies than the average seed startup in the first place. Since the analysis was based on ca. twenty Tier 1 VCs – Benchmark, Sequoia, Union Square etc. – I believe there’s no question that the subset of startups that received seed funding from one of these firms is of much higher quality than the overall average. These firms all have massive deal-flow and are the best firms in the industry. They know how to pick well. I’m sure both (A) and (B) play a role, but since we don’t know the relative impact of the two factors, the statistics don’t answer the question.

2) How confident are you that you’ll have strong traction by the time you want to raise your Series A?

Putting these two factors together gives you a simple matrix:

Here’s how to read the matrix:

Top left: If the level of conviction of BigVC (at the time of the seed investment) is high and your traction (by the time you want to raise your next round) is extremely poor, there’s a chance that BigVC will put in some more money (to give you a chance to figure it out, turn things around, pivot,...). It’s not very likely, but since it’s easier for a large VC than for small investors to finance your company for another six months or so, having a large VC on board might be advantageous if you end up in this cell of the matrix. Based on this logic, my verdict for this scenario is slightly positive (that is, if you expect to end up in this cell, take money from BigVC).

Bottom left: If the level of conviction of BigVC is low and your traction is extremely poor, BigVC will most likely not give you more money and probably nobody else wants to invest neither. In this case, the fact that you’ve raised money from a large VC probably doesn’t matter, but it further reduces the chances of raising from other investors. My verdict: Slightly negative.

Top middle: In the high-conviction / OK-ish traction scenario there’s a decent chance that BigVC will finance the company through a few iterations or pivots, something that is harder to do without a big investor on board. On the flip side, if BigVC does not invest in this scenario, that will create a very bad signal (as explained above) and greatly reduce your chances to raise from other investors. My verdict: Hard to predict, it can go both ways, so let’s say neutral.

Bottom middle: If BigVC invested with little conviction and your traction is OK but not great, it’s very likely that BigVC will not invest further. This is extremely problematic as it creates a bad signal (as explained above) and greatly reduces your chances to raise from other investors. My verdict: Strongly negative.

Top right and bottom right: If you have excellent traction, everything else doesn’t matter that much. If BigVC wants to lead or pre-empt your round, you might save a lot of time (but you might not get the best valuation). If BigVC doesn’t want to invest for some reason, you’ll find other investors, but it will be harder. My verdict: Slightly positive for high-conviction, slightly negative for low-conviction.

If you’ve read until here and you’re more confused than when you started to read, here’s the take-away of the analysis:

If the big VC who wants to invest in your seed round acts with little conviction, i.e. he/she really just wants a cheap option, you’re better off saying no regardless of what kind of traction you expect to have by the time you raise the next round. There’s very little upside but very strong downside. So if you have the opportunity to raise a small amount from a large VC and you know that the fund places dozens or maybe even hundreds of these bets, my advice is to say no.

If the big VC acts with strong conviction, there’s strong upside but also significant risk. In this case I don’t have a general advice, and the right decision depends on the level of conviction of the VC and on the value-add that he/she delivers. There are a few things you can do to to find out more about the strategy and value-add of the investor. First, ask the investor how many seed deals the firm has done in the last years and in how many of these cases they led or strongly participated in the A-round. Second, talk to a number of founders who have received a seed investment from the firm and ask them how it's like to work with the firm. Keep in mind that however you decide, it's an extremely important and irreversible decision - so think through it carefully and do your due diligence.

Saturday, July 16, 2016

In the last few weeks I participated in a few interviews/discussions to talk about SaaS, entrepreneurship, venture capital and related topics that are near and dear to my heart. If you're interested in me rambling about some of my earliest entrepreneurial adventures (hint: C64, Amiga,...) and how I found Zendesk (hint: luck), and if you don't mind listening to a heavy German accent and lots of "UMs" and "HMMs", here you go. :-)

Sunday, June 26, 2016

When founders show me their sales pipeline, the data is typically visualized in some variations of one of these formats:

When I see charts like this, I often find it hard to quickly wrap my head around the data and draw meaningful conclusions. Sometimes, important numbers are missing altogether. In other cases, they are there but are shown on another page or in another report.

I then find myself wonder about questions such as:

The pipeline is growing nicely, but how much are they actually closing?

How long does it take them to move leads through the funnel?

Are they purging their pipeline or are they accumulating a lot of "dead" pipeline value?

With this in mind I tried to come up with a new way for high-level pipeline development visualization, one that makes it easier to quickly get to the key take-aways. If you're interested in the (preliminary) result only, check out this mockup. If you'd like to learn more about my thought process and some additional details, read on.

The key problem that I have with the standard ways of looking at pipeline development is that it's hard to follow how deals move through the funnel. I've always thought that pipeline development charts should work a bit more like a cohort analysis that allows you to follow a customer cohort's development over time, and so I mocked up this:

The "pipes" give you a better understanding of what happened to the leads in a certain stage and month. For example, you can see that of the $1.6M that was in "prospect" stage in January:

$750k (47%) stayed in "prospect" stage

$500k (31%) were moved to the next stage ("demo/trial")

$350k (22%) were lost/purged

The next step was to add a few additional months to the mockup:

This unfortunately made things a little messy, and people will probably feel overwhelmed by the amount of numbers. One solution, if someone decides to build a little application like a Salesforce.com add-on, could be to hide all of the pipe numbers by default and show them on-hover (maybe with an option to show them all at once):

What's still missing are some aggregated key metrics ...

... and a better way to quickly grasp how these numbers have changed month over month:

Here's one mockup with all three elements on it:

What you can quickly see in this example is that this imaginary startup is adding an increasing dollar amount of prospects to the pipeline and keeps closing deals, but the rate at which it moves leads to the bottom of the funnel is declining. At the same time, the percentage of lost deals has been growing slowly, while the percentage of deals that remained in the same stage has increased sharply, indicating an increase in sales cycle and/or a poor job of pipeline purging. This has already led to a shrinking bottom-of-the-funnel pipeline, and if the company can't figure out and fix the cause of that development, it will soon close less and less deals.

All of this is something that you can immediately see by looking at these charts and numbers and which I think is usually harder to see by looking at traditional pipeline charts. What do you think? Looking forward to your comments!

Friday, June 03, 2016

My "SaaS Funding Napkin", published a few days ago, got lots of love on Facebook, Twitter, etc. Thanks everybody! Some people (rightfully) mentioned, though, that the image is hard to read on mobile devices. So if a napkin has a good format for a desktop or laptop screen, which real-world-analogy could be a fit for mobile screens?

Tuesday, May 31, 2016

When we invest in a SaaS startup, which almost always happens at the seed stage, the next big milestone on the company’s roadmap is usually a Series A. If you carry this thought further and assume that the biggest goal after the Series A is to get to the Series B (and so on, you get the idea) it sounds like turtles all the way down. But financing rounds are obviously not a goal in itself. They are a means to a bigger goal. Some SaaS companies got big without raising a lot of capital – Atlassian, Basecamp and Veeva are probably the most famous examples. But they are exceptions, not the rule. According to this analysis of Tomasz Tunguz, the median SaaS company raises $88M before IPO.

Below is my back of a (slightly bigger) napkin answer to this question.

A few important notes:

The assumption of the information in the table is that the founding team is relatively “unproven”. Founding teams with previous large exits under their belts can raise large seed rounds at very high valuations on the back of their track records and a Powerpoint Keynote presentation.

Some of the information is tailored to enterprise-y SaaS companies. If you have a viral product (like Typeform or infogram), some of the “rules” don’t apply.

If you have virality and a proven founder team, you’re Slack and no rules whatsoever apply. :)

Monday, April 11, 2016

For some reason we keep finding great early-stage SaaS startups in France, and it's not because of my command of the French language. In the last few years we've invested in four awesome SaaS companies from France: Algolia, Front, Mention and Critizr. We recently did #5, which hasn't been announced yet, and are in advanced talks with a potential #6. Besides our SaaS investments, we're also proud investors in StarOfService, an online marketplace to hire a wide range of professionals. Something is clearly going on in France, and we like it.

Our good connection to the French startup ecosystem was one of the reasons why we picked France as the first country for our "European SaaS Landscape" project. Another reason was that Clément not only speaks French, he IS French, and knows the market very well.

Without further ado, here it is: an industry map of the most important SaaS startups founded in France.

To learn more about our methodology and some of the insights we got while doing the research, check out Clément's post on Medium. If you have any questions, comments or suggestions, give us a shout!

Wednesday, April 06, 2016

About three years ago, we were looking for an Associate to join Point Nine and put up this landing page:

We called the position "truffle pig", because just like a truffle pig is digging up the best truffles from the ground, we as an early-stage VC try to find the best startups among a large number of potential investments. I have to give full credit for the truffle pig analogy to Mathias Schilling and Thomas Gieselmann of e.ventures, by the way. "Truffle pigs" is what they (young VC Associates at that time) called themselves when they approached my co-founder and me back in 1997 after having stumbled on this website. Fast-forward almost 20 years and we still haven't found a better way to describe the role. :)

Anyway, our search three years ago led to two fantastic truffle pigs, Rodrigo and Mathias, both of whom got promoted to Principals at Point Nine in the meantime. And today we're excited to kick-off the search for a new Associate. Here are all the details.

This is an incredible opportunity for a young, super-smart, super-driven person with outstanding analytical skills and a solid user interface. I'm pretty sure that it took me more than 10 years to get the expertise and network which you'll get during three years in this job.

If you're interested, please take a look at our job ad. If you know somebody who could be great fit, please pass on the link. Thanks!

In case you've started to modify the template already and want to keep working with the previous version, here are the two bugs that you need to correct:

1) Cell U124 on the Costs tab, i.e. the costs for external recruiters in December 2016, contained:

=(W87-U87)*$E$124+X96

The +X96 part has been added accidentally and needs to be removed. So the correct version is:

=(W87-U87)*$E$124

2) Row 55 on the Revenues tab, i.e. the CACs for the Pro plan, is completely wrong. It should be, for column I (with the other columns following analogously):

=0,5*(Costs!J62+Costs!J96+Costs!J104+Costs!J112+Costs!J122)/I49

Once again, apologies for the inconvenience. If I or somebody else finds any other bugs, I will fix them ASAP and update the change log here.

PS: Before you ask – yes, I'm aware that it's ironic that I have to post an on-premise software style bug patch to a SaaS financial planning template. Ironic in an Alanis Morissette kind of way, that is, because "ironic" actually means something completely different. Google it if you don't believe me.

[Update 06/30/2016: I've fixed two further small issues that were reported by two kind readers in the comments below.]

In the last few weeks I've finally found some time to create a "v2" of the template ... just in time for a little Easter gift to the SaaS community. ;-) I'd recommend that you read this post first since it includes some important notes, but if you prefer to check out the template right away click here to download the Excel sheet.

The original v1 model was a very simple plan for early-stage SaaS startups with a low-touch sales model. As I wrote in the original post:

It's a simple plan for an early-stage SaaS startup with a low-touch sales model – a company which markets a SaaS solution via its website, offers a 30 day free trial, gets most of its trial users organically and through online marketing and converts them into paying customer with very little human interaction. Therefore the key drivers of my imaginary startup are organic growth rate, marketing budget and customer acquisition costs, conversion rate, ARPU and churn rate. If you have a SaaS startup with a higher-touch sales model where revenue growth is largely driven by sales headcount, the plan needs to be modified accordingly.

The new version comes with a number of improvements:

Support for multiple pricing tiers

Support for annual contracts with annual pre-payments

Much more solid headcount planning

Better visibility into "MRR movements"

Better cash-flow planning

Charts galore :-)

The downside of these improvements is that the spreadsheet has become significantly larger and more complex, but I tried my best to find the right balance. Also, the vast majority of the numbers in the sheet are calculated and the number of input cells is fairly limited.

The spreadsheet should be pretty self-explanatory but I've included a number of comments in the spreadsheet. Make sure to check them out - some of them are important in order to understand the model (in case you're not familiar with that Excel feature, hover over the little red triangles).

Here are a some additional notes:

1) General comments

The sheet is hot off the press and given the large amount of formulas I can't rule out that there are bugs. If you find one, please email me at and I'll fix it ASAP.

The model contains a lot of simplifications. Don't expect that it will perfectly fit your specific business - consider it a starting point.

2.) "Summary" tab

The "Summary" tab contains only two types of input cells: Your starting bank balance and cash injections from financings. Everything else is calculated, mostly using data from subsequent tabs.

As with all input cells in the model, consider the values that I've put in to be dummy data. Fill those cells with your own data and assumptions.

The model doesn't take into account interest or taxes (except for payroll taxes).

The "Revenues" line shows your end-of-month MRR for the respective month. This is not compliant with the US GAAP definition of "revenues", which uses different revenue recognition rules, but since SaaS companies live and breathe MRR I think it's the right approach for a SaaS financial model.

3.) "Revenues" tab

The model assumes that you have three pricing tiers. I've called them "Basic", "Pro" and "Enterprise". If you have more or fewer pricing plans you can of course adjust the model accordingly (with some effort). It is further assumed that all Basic and Pro customers are on monthly plans and that all Enterprise customers are on annual plans.

The model assumes that you're getting signups organically and via paid marketing and that you're converting a percentage of them into Basic customers and Pro customers. You can change the key assumptions such as your organic growth rate and your conversion rates in the grey area on the left.

The Enterprise customer segment follows a different logic, based on the assumption that Enterprise customer acquisition is sales-driven as opposed to the marketing-driven low-touch sales model for Basic and Pro customers. The key drivers in the Enterprise segment of the model are your revenue targets, sales team quotas and your assumptions for churn and upsells.

The spreadsheet shows the impact of e.g. Basic customers who upgrade to Pro and Pro customers who upgrade to Enterprise, but to keep things simple it doesn't support each and every possible movement between plans. For example, I didn't include the option for Basic customers to upgrade to Enterprise straight away or for Enterprise customers to downgrade. If this is a relevant factor in your business, you can of course accommodate for that by adding a few extra rows.

For Basic and Pro customers, the model allows you to project ARPA development using a given ARPA at the beginning of the planning period along with assumptions on monthly ARPA increases. For Enterprise customers, the model assumes pricing increases at the time of renewal but not during the term of the subscription. Depending on your specific pricing model you'll have to modify that, e.g. to allow for Enterprise customers to add more seats continuously.

In order to be able to calculate churn for Enterprise customers in the 1st year of the plan, it is assumed that existing Enterprise customers have been acquired over the course of the previous 12 months. This is of course a somewhat theoretical assumption and you need to adjust the model to include your actual numbers.

As you can see in one of the charts below the numbers, the model allows you to calculate your "MRR movements". It's worth pointing out that the model currently doesn't show "Expansion MRR" and "Contraction MRR" separately but only the delta of the two, which I've called "Net Expansion MRR". In order to calculate Expansion MRR and Contraction MRR separately I'd have to add a couple of additional rows. To avoid making things too complicated, I decided against doing that for now. Fortunately ChartMogul (a Point Nine portfolio company, sorry for the plug) makes it super easy to drill down into all of your MRR movements.

Please note that the CAC data and "CAC payback time" calculation are based on pretty crude simplifications. A solid planning of CAC payback times, CAC/LTV ratios etc. would require a lot of additional input data.

In order to adjust headcount planning in the G&A, R&D and marketing departments, change the assumptions for start date, base salary and bonus in the grey "Assumptions" area. You can remove, change or add roles in column H.

With the exception of the VP of Sales role, sales staff headcount planning is done on the separate "Sales Team Hiring Plan" tab (re-using a model that I've built for this post). It calculates the number of sales people that you need based on the growth targets for your Enterprise customer segment, the quota of your sales people and a few other variables.

Headcount planning for the Customer Success team is (again with the exception of the VP) done formulaically as well, based on assumptions on how many customers a customer success team member can handle.

It is assumed that there's only one team, which I've called Customer Success, which does both customer support and customer success. Many SaaS companies have different teams for the two functions; if you're one of them you can adjust the plan accordingly.

The costs for the Customer Success team are attributed to CoGS. This is debatable – if your Customer Success team plays an important role in converting signups or upselling customers you should consider allocating at least a portion of these costs to S&M and include those costs in your CACs. Please note that changing the "cost type" in column I will not automatically move the costs to a different category on the "Summary" tab so you'll have to do that manually.

The model assumes that payroll tax is the same for all employees. This may have to be adjusted, e.g. if you have people in different countries.

Regarding the cash impact of expenses, the model assumes that:

payroll taxes are paid monthly

bonuses are paid yearly (except for the sales team)

sales team bonuses are paid quarterly (since bonuses/commissions play a much stronger role in sales compared to other departments)

The model (somewhat simplistically) assumes that there are no capital expenditures. If you make investments into things like servers, computers or office furniture you should add these expenses accordingly.

If you've made it this far and haven't downloaded the Excel sheet yet: Here it is.

If you have any questions, comments or suggestions, let me know in the comments or email me. And if you like the model, tweet it out. :)

Finally, big thanks to Chris Amani, Sr. Finance Director at Humanity, as well as to Pawel and Dominik of Point Nine, for reviewing drafts of the model and for providing valuable feedback.

Friday, March 11, 2016

Judging from the number of Facebook likes and retweets, as well as comments on Twitter and elsewhere, my last post resonated with quite a lot of people. Some people thought it was provocative though, and some chimed in with good feedback:

Therefore I thought it would be worth following up on the topic to make sure that my message is clear.

The provocative sentence, I think, was this one:

"Building a SaaS business with $1-2 million in ARR is not that hard and not that valuable."

It's important to point out that I took it back in the next sentence ...

"Let me rephrase that. Starting a new company is always hard and most SaaS startups never get to $1-2 million in ARR. Every founder who accomplishes this deserves a huge amount of respect."

... and tried to explain the real point I was trying to make in the next one:

"The point is that getting to $1-2 million in ARR probably has less predictive value concerning a company’s ability to get to true scale than most people think – or at least thought some years ago."

As you can see, I don't disagree at all with Jonathan Abrams' s comment that building any business is hard. The reason why I wrote the sentence above, only to rephrase it in the following sentence, was that it was a reference to Josh Hannah's post about "nice little $40M eCommerce companies", which my post was inspired by.

To be as clear as possible about the subject, let me sum up my view again:

1) Building any business is hard. It requires a much broader skill set, more hard work and much more persistence than most normal jobs. (Let me refine that to "normal office jobs" - I don't want to get into an argument with heart surgeons or firefighters.) And since most businesses fail (at least when it comes to tech startups) it also requires a huge tolerance for risk.

2) Getting a SaaS company from 0 to $1-2M in ARR is hard. For the reasons mentioned in the original post, I think it has become significantly easier in the last 5-10 years but that doesn't mean that it isn't still very hard. Maybe a better way to put it would be "more likely" than "easier".

3) As hard as it is to get to $1-2M in ARR, getting to that level doesn't say much about a company's ability to get to $100M in ARR. For most companies which didn't raise venture capital this is completely irrelevant. If you're a bootstrapped company or raised only a small amount of outside funding and eventually get to a few million dollars in ARR that's an amazing outcome, and calling a company like this a "lifestyle business" is ignorant and stupid. If you're a VC-funded company, the prospects of getting to $100M matter, though – at least to some of your shareholders. :)

In case it's still not clear, maybe this funnel diagram helps to explain what I mean. :-)

Saturday, February 20, 2016

About two years ago, Josh Hannah of Matrix Partners wrote an excellent article titled “That's a nice little $40M eCommerce company you have there. Call me when it scales.” In it he argues that an eCommerce business with $10 to $20 million in revenues is not that hard to build and also not very valuable. I would recommend that you read the full article, but one of the key points of the article was that if you fill a niche and have distinctive product/market fit with a set of customers, you can acquire customers very cheaply - up until a certain point, when you’ve maxed out the cheap customer acquisition channels and need to tap into more scalable channels. At that point it becomes a lot harder because the next set of customer acquisition channels will likely be much more expensive.

As a side note I’d add that the value of an eCommerce business with $10-20 million in revenue can be even more deceptive if a company has burned a lot of money to get to this level and has very low (or even negative) gross margins. The reason is that in most categories online shopping has become ultra-transparent (something which I’m not completely innocent of ;-) ) and that there’s a group of highly price-sensitive customers which always goes for the lowest price. So if you start an online shop, offer products at a loss, get listed on some of the biggest comparison shopping sites and do some affiliate marketing, you can easily get to tens of millions in revenue.

Now let’s talk about SaaS. In the last few years I’ve come to the realization that Josh’s observation can also be applied to the SaaS world: Building a SaaS business with $1-2 million in ARR is not that hard and not that valuable. Let me rephrase that. Starting a new company is always hard and most SaaS startups never get to $1-2 million in ARR. Every founder who accomplishes this deserves a huge amount of respect. The point is that getting to $1-2 million in ARR probably has less predictive value concerning a company’s ability to get to true scale than most people think – or at least thought some years ago.

The reason, I think, is that over the last 5-10 years it has become much easier to build a SaaS product and get initial traction:

Building a web application has become much easier, faster and cheaper. Whether starting an Internet startup has really become 10x cheaper depends on how exactly you phrase the question and is debatable. But creating and launching a SaaS product has without a doubt become much cheaper in the last ten years. Moore’s Law, cheaper hardware and more bandwidth are one factor, but the even more important factor is that today there are great products for so many of the issues which the previous generation of SaaS founders had to worry about (billing, analytics, server monitoring, application performance, live chat, to name just a few … even AWS didn’t exist 10 years ago!).

Ten years ago, there was nobody who SaaS founders could ask in order to learn how to do, for example, inbound marketing, low-touch sales or customer success. Many of the tactics that everybody is using today hadn’t been invented yet. In the last ten years the playbook has been written and subsequently published. As I wrote in my post about the rising table stakes in SaaS, today an abundance of knowledge about any imaginable SaaS topic is readily available online and events like the fantastic SaaStr conference last week allow founders to learn from people who’ve done it before.

As SaaS is quickly becoming the norm, it’s now much easier to get initial traction. In any given category, the number of potential customers who considers (and in most cases prefers) a SaaS solution is much higher than it was some years ago. This and the fact that almost everybody owns a smartphone today has given rise to new categories which previously weren’t software categories at all because people used pen and paper to get the job done.

So – it has become much easier to develop and launch a SaaS application and get initial traction, but if you have product/market fit in a small niche, which many SaaS companies do, it may be very hard to expand beyond that niche. And even if your market is large in principle, keeping growth up after you’ve picked the low-hanging fruits and reached a few million dollars in ARR will become increasingly difficult. In order to go from a $1-2 million in ARR to $10 million and eventually $100 million, you’ll have to find highly repeatable and reasonably profitable ways to acquire customers at huge scale. With few exceptions that means you either need to have a viral product (a.k.a. as hunting mice) or you have to go upmarket and dramatically increase your ACV over time.

Some SaaS businesses manage to do this and have a shot at building a $100 million ARR company, but for the majority of SaaS companies growth will taper off once they’ve reached a few million dollars in ARR, making it hard to ever grow significantly beyond $10-20 million. In a way, this isn’t surprising – not everyone can become a unicorn. :-) The non-trivial part of what I’m saying is that 5-10 years ago, many of these companies wouldn’t have gotten to a few million dollars in ARR. Put differently, there are more $100 million ARR SaaS companies today, but the number of companies in the $1-10 million ARR range has grown disproportionately faster. That’s my theory at least, it’s not scientifically proven.

If my theory is true, will this be bad news for people in the SaaS industry? It’ll depend on who you ask. It could make seed and Series A investing harder because the percentage of seed and Series A funded SaaS startups that becomes really big would decrease - and VCs need large outcomes in order to make their business model work. But it would also lead to the generation of a large number of small-ish but still very viable SaaS businesses, many of which could generate very decent profits for their founders. From that point of view, there’s never been a better time to start a SaaS company.

PS: You may have noticed that I’ve changed Josh’s “call me when it scales” to “call me to to discuss if it will scale”. Being a seed investor I’m trying to find SaaS companies that can scale before they have scaled.

PPS: If you’re wondering why Josh talks about revenues in the $10-40 million range when he refers to sub-scale companies while I talk about $1-2 million in ARR: The reason is that besides the fact that SaaS revenues are recurring, SaaS margins are almost an order of magnitude higher than eCommerce margins. $1 in SaaS revenues is much more valuable than $1 in eCommerce revenues (all revenue is not created equal!).